Abstract Molecular imaging is critical for characterizing dynamic changes in tumor, tumor microenvironment (MTE), and tumor-stroma interactions at multiscale levels. Metastatic liver cancers that originate from different primary sites (i.e., breast, colon and uveal melanoma (UM)) share common pathological nodular and infiltrative patterns, but differential expressions of multiple key biomarkers that respond to different types of therapy. Imaging these differential pathological growth patterns non-invasively is a significant unmet medical need. However, precision molecular imaging via MRI has been hindered by a lack of safe and effective MRI contrast agents and methods. The goal of this project is to advance and validate the multi-color capability of precision molecular MR Imaging (pMRIm) for simultaneous quantification of multiple molecular biomarkers within the native tumor environment to allow for early detection of metastases and to provide guided therapy tailored to a set of liver molecular signatures. Our preliminary histological analyses of human liver metastases have provided the first evidence that CXCR4, VEGFR, and collagen I exhibit changes of metastatic potential, angiogenesis, and the micro- environment during cancer initiation and progression in UM liver metastasis mouse models. Aim 1 is to develop ?multi-color? protein molecular contrast agents (ProCAsm) for simultaneous quantification of multiple biomarkers. We will determine metal binding affinities and selectivities as well target binding capability using various methods. We will develop and validate relaxation properties and multi-contrast capability under different field strengths using multiple-contrast Magnetic Resonance Fingerprinting Methodology (MC-MRF). Aim 2 is to develop and validate multi-color molecular MR imaging methodology (pMRIm) in multiple cell lines and explanted liver. The sensitivity and specificity of quantification of multiple biomarker cellular expression by pMRIm will be determined and compared with fluorescence and histological analysis.